Chord Bunch Walks for Recognizing Naturally Self-Overlapped and Compound Leaves

EFFECTS OF STRETCHING ON LOWER LIMB STRENGTH IN BASKETBALL ATHLETES

ABSTRACT Introduction: Basketball players depend on excellent explosive power in the lower limbs for training and competition activities such as starting, braking, accelerating, decelerating, running, and jumping instantly and quickly. The level of Chinese athletes in this aspect is lower than world powers, and formulating training focused on explosive strength can enhance the training of these athletes. Objective: Study the effects of stretching on lower limb strength in basketball athletes. Methods: 20 young male basketball players selected as volunteers for the research were randomly divided into an experimental and control group, with 10 people in each group for retrospective analysis. The effect of rapid stretching compound training on the explosive power of lower limbs in basketball players was evaluated using the comparative method of literature data, expert interviews, experimental methods, and mathematical statistics. Results: After 8 weeks of training, the scores of each test index in the control group were significantly improved, including the standing jump and long-distance scores (P < 0.01). Unipodal takeoff and post-run long-range scores were significantly improved (P < 0.05). Conclusion: Both traditional resistance and compound lower limb stretching training can improve explosive power in young basketball players, but compound training showed more prominent results. Level of evidence II; Therapeutic studies - investigation of treatment outcomes.

Fast Shape Recognition via the Restraint Reduction of Bone Point Segment

In computer science, and especially in computer vision, the contour of an object is used to describe its features; thus, the shape descriptor plays an indispensable role in target detection and recognition. Further, Fourier is an important mathematical description method, and the Fourier transform of a shape contour has symmetry. This paper will demonstrate the symmetry of shape contour in the frequency domain. In recent years, increasing numbers of shape descriptors have come to the fore, but many descriptors ignore the details of shape. It is found that the most fundamental reason affecting the performance of shape descriptors is structural restraints, especially feature structure restraint. Therefore, in this paper, the restraint of feature structure that intrinsically deteriorates recognition performance is shown, and a fast shape recognition method via the Bone Point Segment (BPS) restraint reduction is proposed. An approach using the inner distance to find bone shapes and segment the shape contour by these bones is proposed. Then, Fourier transform is performed on each segment to form the shape feature. Finally, the restraints of the shape feature are reduced in order to build a more effective shape feature. What is commendable is that its discriminability and robustness is strong, the process is simple, and matching speed is fast. More importantly, the experiment results show that the shape descriptor has higher recognition accuracy and the matching speed runs up to more than 1000 times faster than the existing description methods like CBW and TCD. More importantly, it is worth noting that the recognition accuracy approaches 100% in the self-build dataset.